| 来源类型 | Working Paper |
| 规范类型 | 报告 |
| DOI | 10.3386/w27023 |
| 来源ID | Working Paper 27023 |
| Estimating the COVID-19 Infection Rate: Anatomy of an Inference Problem | |
| Charles F. Manski; Francesca Molinari | |
| 发表日期 | 2020-04-20 |
| 出版年 | 2020 |
| 语种 | 英语 |
| 摘要 | As a consequence of missing data on tests for infection and imperfect accuracy of tests, reported rates of population infection by the SARS CoV-2 virus are lower than actual rates of infection. Hence, reported rates of severe illness conditional on infection are higher than actual rates. Understanding the time path of the COVID-19 pandemic has been hampered by the absence of bounds on infection rates that are credible and informative. This paper explains the logical problem of bounding these rates and reports illustrative findings, using data from Illinois, New York, and Italy. We combine the data with assumptions on the infection rate in the untested population and on the accuracy of the tests that appear credible in the current context. We find that the infection rate might be substantially higher than reported. We also find that the infection fatality rate in Italy is substantially lower than reported. |
| 主题 | Econometrics ; Estimation Methods ; Health, Education, and Welfare ; Health ; COVID-19 |
| URL | https://www.nber.org/papers/w27023 |
| 来源智库 | National Bureau of Economic Research (United States) |
| 引用统计 | |
| 资源类型 | 智库出版物 |
| 条目标识符 | http://119.78.100.153/handle/2XGU8XDN/584695 |
| 推荐引用方式 GB/T 7714 | Charles F. Manski,Francesca Molinari. Estimating the COVID-19 Infection Rate: Anatomy of an Inference Problem. 2020. |
| 条目包含的文件 | ||||||
| 文件名称/大小 | 资源类型 | 版本类型 | 开放类型 | 使用许可 | ||
| w27023.pdf（258KB） | 智库出版物 | 限制开放 | CC BY-NC-SA | 浏览 | ||
除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。
